{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. 定义算法"
   ]
  },
  {
   "attachments": {
    "sarsa_pseu.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 算法流程\n",
    "\n",
    "如图所示，$\\text{Sarsa}$ 算法流程跟 $\\text{Q-learning}$ 算法基本相同，主要区别在于 $\\text{Sarsa}$ 算法使用的是智能体实际执行的动作 $a'$ 来更新动作价值函数，而不是选择的最大动作值。\n",
    "\n",
    "![sarsa_pseu.png](attachment:sarsa_pseu.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义超参数\n",
    "\n",
    "为了便于调整和实验，我们把所有的超参数都定义在一个`Python`类中，如代码所示。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Config:\n",
    "    def __init__(self) -> None:\n",
    "        ## 通用参数\n",
    "        self.env_id = \"CliffWalking-v0\" # 环境id\n",
    "        self.n_states = 48 # 状态数\n",
    "        self.n_actions = 4 # 动作数\n",
    "        self.render_mode = None # 渲染模式\n",
    "        self.algo_name = \"Sarsa\" # 算法名称\n",
    "        self.seed = 1 # 随机种子\n",
    "        self.device = \"cuda\" # 训练设备，\"cpu\" or \"cuda\"\n",
    "        self.max_episode = 500 # 最大回合数\n",
    "        self.max_step = 200 # 每个回合的最大步数\n",
    "\n",
    "        ## 算法参数\n",
    "        self.epsilon_start = 0.95 # epsilon 初始值\n",
    "        self.epsilon_end = 0.01 # epsilon 终止值\n",
    "        self.epsilon_decay = 300 # epsilon 衰减率\n",
    "        self.gamma = 0.90 # 奖励折扣因子\n",
    "        self.lr = 0.1 # 学习率"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义策略\n",
    "\n",
    "在 $\\text{Sarsa}$ 算法中，我们同样使用 $\\epsilon$-贪婪策略来选择动作。具体实现与 $\\text{Q-learning}$ 算法中的实现相同。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import math\n",
    "from collections import defaultdict\n",
    "\n",
    "class Policy(object):\n",
    "    def __init__(self, cfg: Config):\n",
    "        ''' 初始化\n",
    "        '''\n",
    "        self.n_actions: int = cfg.n_actions # 动作数\n",
    "        self.lr: float = cfg.lr \n",
    "        self.gamma: float = cfg.gamma    \n",
    "        self.epsilon: float = cfg.epsilon_start\n",
    "        self.sample_count = 0  # 采样计数，用于 epsilon 衰减\n",
    "        self.epsilon_start: float = cfg.epsilon_start \n",
    "        self.epsilon_end: float = cfg.epsilon_end\n",
    "        self.epsilon_decay: float = cfg.epsilon_decay\n",
    "        self.Q_table = defaultdict(lambda: np.zeros(self.n_actions)) # 使用默认字典来表示 Q(s,a)，初始值为 0\n",
    "\n",
    "    def sample_action(self, state):\n",
    "        ''' 采样动作\n",
    "        ''' \n",
    "        self.sample_count += 1\n",
    "        # epsilon 值需要衰减，衰减方式可以是线性、指数等，以平衡探索和开发\n",
    "        self.epsilon = self.epsilon_end + (self.epsilon_start - self.epsilon_end) * \\\n",
    "            math.exp(-1. * self.sample_count / self.epsilon_decay) \n",
    "        if np.random.uniform(0, 1) > self.epsilon:\n",
    "            action = np.argmax(self.Q_table[str(state)]) # 选择具有最大 Q 值的动作\n",
    "        else:\n",
    "            action = np.random.choice(self.n_actions) # 随机选择一个动作\n",
    "        return action\n",
    "    \n",
    "    def predict_action(self, state):\n",
    "        ''' 预测动作\n",
    "        '''\n",
    "        action = np.argmax(self.Q_table[str(state)])\n",
    "        return action\n",
    "\n",
    "    def update(self, state, action, reward, next_state, next_action, done):\n",
    "        ''' 更新策略\n",
    "        '''\n",
    "        Q_estimate = self.Q_table[str(state)][action]\n",
    "        if done:\n",
    "            Q_target = reward  # 终止状态 \n",
    "        else:\n",
    "            Q_target = reward + self.gamma * self.Q_table[str(next_state)][next_action] # 与 Q-learning 的唯一区别\n",
    "        self.Q_table[str(state)][action] += self.lr * (Q_target - Q_estimate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## 定义工具函数\n",
    "\n",
    "为了保证实验的可复现性，通常需要固定随机种子。因此，我们定义一个工具函数 `set_seed` 来设置所有相关模块的随机种子。另外，为了更好地观察训练过程中的变化情况，我们定义了一些绘图函数来可视化训练结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import os\n",
    "import torch\n",
    "import seaborn as sns; sns.set_theme()\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def set_seed(seed = 0):\n",
    "    ''' 固定随机种子\n",
    "    '''\n",
    "    if seed == 0: # 不设置随机种子\n",
    "        return \n",
    "    np.random.seed(seed)\n",
    "    random.seed(seed)\n",
    "    torch.manual_seed(seed)\n",
    "    torch.cuda.manual_seed(seed) \n",
    "    os.environ['PYTHONHASHSEED'] = str(seed)\n",
    "    # config for cudnn\n",
    "    torch.backends.cudnn.deterministic = True\n",
    "    torch.backends.cudnn.benchmark = False\n",
    "    torch.backends.cudnn.enabled = False\n",
    "\n",
    "def smooth(data, weight=0.9):  \n",
    "    '''用于平滑曲线\n",
    "    '''\n",
    "    last = data[0] \n",
    "    smoothed = []\n",
    "    for point in data:\n",
    "        smoothed_val = last * weight + (1 - weight) * point  # 计算平滑值\n",
    "        smoothed.append(smoothed_val)                    \n",
    "        last = smoothed_val                                \n",
    "    return smoothed\n",
    "\n",
    "def plot_rewards(rewards, ylabel = \"rewards\", title=\"learning curve\"):\n",
    "    ''' 绘制奖励曲线\n",
    "    '''\n",
    "    sns.set_theme()\n",
    "    plt.figure()  \n",
    "    plt.title(f\"{title}\") # 设置标题\n",
    "    plt.xlim(0, len(rewards)) # x轴范围\n",
    "    plt.xlabel('episodes') # x轴标签\n",
    "    plt.ylabel(ylabel) # y轴标签\n",
    "    plt.plot(rewards, label='original') # 绘制原始奖励曲线\n",
    "    plt.plot(smooth(rewards), label='smoothed') # 绘制平滑后的奖励曲线\n",
    "    plt.legend() # 显示图例\n",
    "    plt.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义环境\n",
    "\n",
    "同 $\\text{Q-learning}$ 算法一样，我们使用 `OpenAI Gym` 提供的 `CliffWalking-v0` 环境来测试 $\\text{Sarsa}$ 算法的性能表现。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gymnasium as gym\n",
    "\n",
    "ACTION_MAP = {0: 'Up', 1: 'Right', 2: 'Down', 3: 'Left'}\n",
    "\n",
    "def create_env(cfg: Config):\n",
    "    ''' 创建环境并设置随机种子\n",
    "    '''\n",
    "    env = gym.make(cfg.env_id, render_mode = cfg.render_mode) # 创建环境\n",
    "    n_states = env.observation_space.n\n",
    "    n_actions = env.action_space.n\n",
    "    setattr(cfg, 'n_states', n_states)\n",
    "    setattr(cfg, 'n_actions', n_actions)\n",
    "    print(f\"状态数：{n_states}，动作数：{n_actions}\")\n",
    "    return env"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义训练与测试\n",
    "\n",
    "我们定义了 `train` 和 `test` 函数来分别进行训练和测试。在训练过程中，智能体根据当前策略选择动作，并根据环境反馈更新动作价值函数。在测试过程中，智能体使用贪婪策略选择动作，以评估学习到的策略的性能。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "def train(cfg: Config, env, policy: Policy):\n",
    "    ''' 训练\n",
    "    '''\n",
    "    print(\"开始训练！\")\n",
    "    s_t = time.time()\n",
    "    rewards = []  # 记录所有回合的奖励\n",
    "    steps = []  # 记录所有回合的步数\n",
    "    for i_ep in range(cfg.max_episode):\n",
    "        ep_reward = 0  # 单回合总奖励\n",
    "        ep_step = 0\n",
    "        state, info = env.reset(seed = cfg.seed)  # 重置环境并获取初始状态\n",
    "        action = policy.sample_action(state)  # 采样动作 \n",
    "        for _ in range(cfg.max_step):\n",
    "            ep_step += 1\n",
    "            next_state, reward, terminated, truncated , info = env.step(action)  # 更新环境并返回新状态、奖励、终止状态、截断标志和其他信息（使用 OpenAI Gym 的 new_step_api）\n",
    "            next_action =  policy.sample_action(next_state)\n",
    "            done = terminated or truncated\n",
    "            policy.update(state, action, reward, next_state, next_action, done)  # 更新 policy\n",
    "            state = next_state  # 更新状态 \n",
    "            action = next_action # 更新动作\n",
    "            ep_reward += reward \n",
    "            ep_step += 1\n",
    "            if done:\n",
    "                break\n",
    "        rewards.append(ep_reward)\n",
    "        steps.append(ep_step)\n",
    "        if (i_ep + 1) % 10 == 0:\n",
    "            print(f\"回合：{i_ep+1}/{cfg.max_episode}，奖励：{ep_reward:.2f}, 步数：{ep_step}\")\n",
    "    env.close()\n",
    "    print(f\"完成训练！用时：{time.time()-s_t:.2f} 秒\")\n",
    "    return {'rewards':rewards, 'steps':steps}\n",
    "\n",
    "def test(cfg: Config, env, policy: Policy):\n",
    "    print(\"开始测试！\")\n",
    "    rewards = []  # 记录所有回合的奖励\n",
    "    steps = []\n",
    "    s_t = time.time()\n",
    "    for i_ep in range(cfg.max_episode):\n",
    "        ep_reward = 0  # 一轮的累计奖励 \n",
    "        ep_step = 0\n",
    "        state, info = env.reset(seed = cfg.seed)  # 重置环境并获取初始状态\n",
    "        action_sequence = []\n",
    "        for _ in range(cfg.max_step):\n",
    "            action = policy.predict_action(state)  # 预测动作\n",
    "            next_state, reward, terminated, truncated , info = env.step(action)\n",
    "            done = terminated or truncated\n",
    "            state = next_state  # 更新状态 \n",
    "            action_sequence.append(ACTION_MAP[action])\n",
    "            ep_reward += reward  # 增加奖励\n",
    "            ep_step += 1\n",
    "            if done:\n",
    "                break\n",
    "        steps.append(ep_step)\n",
    "        rewards.append(ep_reward)\n",
    "        print(f\"回合：{i_ep+1}/{cfg.max_episode}，奖励：{ep_reward:.2f}, 步数：{ep_step}, 动作序列：{action_sequence}\")\n",
    "    print(f\"完成测试！用时：{time.time()-s_t:.2f} 秒\")\n",
    "    env.close()\n",
    "    return {'rewards':rewards, 'steps':steps}"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 开始训练\n",
    "\n",
    "定义好以上各个部分后，我们就可以开始训练智能体了。训练过程中，我们会记录每个回合的总奖励和步数，以便后续分析和可视化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "状态数：48，动作数：4\n",
      "开始训练！\n",
      "回合：10/500，奖励：-195.00, 步数：390\n",
      "回合：20/500，奖励：-67.00, 步数：134\n",
      "回合：30/500，奖励：-115.00, 步数：230\n",
      "回合：40/500，奖励：-43.00, 步数：86\n",
      "回合：50/500，奖励：-87.00, 步数：174\n",
      "回合：60/500，奖励：-27.00, 步数：54\n",
      "回合：70/500，奖励：-39.00, 步数：78\n",
      "回合：80/500，奖励：-51.00, 步数：102\n",
      "回合：90/500，奖励：-90.00, 步数：180\n",
      "回合：100/500，奖励：-49.00, 步数：98\n",
      "回合：110/500，奖励：-45.00, 步数：90\n",
      "回合：120/500，奖励：-27.00, 步数：54\n",
      "回合：130/500，奖励：-41.00, 步数：82\n",
      "回合：140/500，奖励：-21.00, 步数：42\n",
      "回合：150/500，奖励：-45.00, 步数：90\n",
      "回合：160/500，奖励：-33.00, 步数：66\n",
      "回合：170/500，奖励：-23.00, 步数：46\n",
      "回合：180/500，奖励：-21.00, 步数：42\n",
      "回合：190/500，奖励：-37.00, 步数：74\n",
      "回合：200/500，奖励：-29.00, 步数：58\n",
      "回合：210/500，奖励：-28.00, 步数：56\n",
      "回合：220/500，奖励：-25.00, 步数：50\n",
      "回合：230/500，奖励：-23.00, 步数：46\n",
      "回合：240/500，奖励：-17.00, 步数：34\n",
      "回合：250/500，奖励：-19.00, 步数：38\n",
      "回合：260/500，奖励：-19.00, 步数：38\n",
      "回合：270/500，奖励：-15.00, 步数：30\n",
      "回合：280/500，奖励：-15.00, 步数：30\n",
      "回合：290/500，奖励：-15.00, 步数：30\n",
      "回合：300/500，奖励：-13.00, 步数：26\n",
      "回合：310/500，奖励：-23.00, 步数：46\n",
      "回合：320/500，奖励：-19.00, 步数：38\n",
      "回合：330/500，奖励：-17.00, 步数：34\n",
      "回合：340/500，奖励：-17.00, 步数：34\n",
      "回合：350/500，奖励：-19.00, 步数：38\n",
      "回合：360/500，奖励：-15.00, 步数：30\n",
      "回合：370/500，奖励：-15.00, 步数：30\n",
      "回合：380/500，奖励：-17.00, 步数：34\n",
      "回合：390/500，奖励：-15.00, 步数：30\n",
      "回合：400/500，奖励：-21.00, 步数：42\n",
      "回合：410/500，奖励：-15.00, 步数：30\n",
      "回合：420/500，奖励：-15.00, 步数：30\n",
      "回合：430/500，奖励：-15.00, 步数：30\n",
      "回合：440/500，奖励：-15.00, 步数：30\n",
      "回合：450/500，奖励：-15.00, 步数：30\n",
      "回合：460/500，奖励：-15.00, 步数：30\n",
      "回合：470/500，奖励：-21.00, 步数：42\n",
      "回合：480/500，奖励：-15.00, 步数：30\n",
      "回合：490/500，奖励：-17.00, 步数：34\n",
      "回合：500/500，奖励：-15.00, 步数：30\n",
      "完成训练！用时：0.12 秒\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "cfg = Config()\n",
    "set_seed(cfg.seed)\n",
    "env = create_env(cfg)\n",
    "policy = Policy(cfg)\n",
    "train_res = train(cfg, env, policy)\n",
    "plot_rewards(train_res['rewards'], title=f\"{cfg.algo_name} on {cfg.env_id} - Training\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 开始测试\n",
    "\n",
    "训练完成后，为了评估智能体的性能，我们进行测试。在测试过程中，智能体使用训练好的动作价值函数来选择最优动作，即不包含探索机制。我们同样会与环境交互，并记录每一轮的奖励和步数，最后进行可视化展示。在复杂环境中，奖励的波动可能较大，而且有时曲线收敛后可能不也不一定代表策略最优（例如奖励设置不当的情况），因此需要渲染环境来直观观察智能体的行为表现。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "状态数：48，动作数：4\n",
      "开始测试！\n",
      "回合：1/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：2/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：3/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：4/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：5/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：6/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：7/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：8/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：9/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "回合：10/10，奖励：-15.00, 步数：15, 动作序列：['Up', 'Up', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Right', 'Down', 'Down']\n",
      "完成测试！用时：0.00 秒\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg.max_episode = 10 # 测试时只跑10个回合\n",
    "# cfg.render_mode = 'human' # 测试时渲染环境, 不要在Notebook中开启渲染，会卡死\n",
    "env_test = create_env(cfg)\n",
    "test_res = test(cfg, env_test, policy)\n",
    "plot_rewards(test_res['rewards'], title=f\"{cfg.algo_name} on {cfg.env_id} - Testing\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "joyrl-book",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
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